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      HBase
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        <h2 id="基本简介"><a href="#基本简介" class="headerlink" title="基本简介"></a>基本简介</h2><p>HBase是一个分布式的、面向列的开源数据库，该技术来源于 Fay Chang 所撰写的Google论文”Bigtable:一个结构化数据的分布式存储系统”。就像Bigtable利用了Google文件系统(File System)所提供的分布式数据存储一样，HBase在Hadoop之上提供了类似于Bigtable的能力。HBase是Apache的Hadoop项目的子项目。HBase不同于一般的关系数据库，它是一个适合于非结构化数据存储的数据库。另一个不同的是HBase基于列的而不是基于行的模式。</p>
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<h2 id="结构介绍"><a href="#结构介绍" class="headerlink" title="结构介绍"></a>结构介绍</h2><p>HBase – Hadoop Database，是一个高可靠性、高性能、面向列、可伸缩的分布式存储系统，利用HBase技术可在廉价PC Server上搭建起大规模结构化存储集群。</p>
<p>与FUJITSU Cliq等商用大数据产品不同，HBase是Google Bigtable的开源实现，类似Google Bigtable利用GFS作为其文件存储系统，HBase利用Hadoop HDFS作为其文件存储系统;Google运行MapReduce来处理Bigtable中的海量数据，HBase同样利用Hadoop MapReduce来处理HBase中的海量数据;Google Bigtable利用 Chubby作为协同服务，HBase利用Zookeeper作为对应。</p>
<p>上图描述Hadoop EcoSystem中的各层系统。其中,HBase位于结构化存储层，Hadoop HDFS为HBase提供了高可靠性的底层存储支持，Hadoop MapReduce为HBase提供了高性能的计算能力，Zookeeper为HBase提供了稳定服务和failover机制。</p>
<p>此外，Pig和Hive还为HBase提供了高层语言支持，使得在HBase上进行数据统计处理变的非常简单。 Sqoop则为HBase提供了方便的RDBMS数据导入功能，使得传统数据库数据向HBase中迁移变的非常方便。</p>
<h2 id="访问接口"><a href="#访问接口" class="headerlink" title="访问接口"></a>访问接口</h2><ol>
<li><p>Native Java API，最常规和高效的访问方式，适合Hadoop MapReduce Job并行批处理HBase表数据</p>
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<li><p>HBase Shell，HBase的命令行工具，最简单的接口，适合HBase管理使用</p>
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<li><p>Thrift Gateway，利用Thrift序列化技术，支持C++，PHP，Python等多种语言，适合其他异构系统在线访问HBase表数据</p>
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<li><p>REST Gateway，支持REST 风格的Http API访问HBase, 解除了语言限制</p>
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<li><p>Pig，可以使用Pig Latin流式编程语言来操作HBase中的数据，和Hive类似，本质最终也是编译成MapReduce Job来处理HBase表数据，适合做数据统计</p>
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<li><p>Hive，当前Hive的Release版本尚没有加入对HBase的支持，但在下一个版本Hive 0.7.0中将会支持HBase，可以使用类似SQL语言来访问HBase</p>
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